author = "Cintra, Rosangela Saher Correa and Silva, Jos{\'e} 
                         Dem{\'{\i}}sio Sim{\~o}es",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)}",
                title = "Artificial Neural Network to estimate Integrated Water Vapor using 
                         satellite data from HSB sensor",
            booktitle = "Proceedings...",
                 year = "2006",
               editor = "Vera, Carolina and Nobre, Carlos",
                pages = "11--15",
         organization = "International Conference on Southern Hemisphere Meteorology and 
                         Oceanography, 8. (ICSHMO).",
            publisher = "American Meteorological Society (AMS)",
              address = "45 Beacon Hill Road, Boston, MA, USA",
             keywords = "integrated water vapor, satellite data, artificial neural network, 
                         brightness temperature, multilayer percepton.",
             abstract = "Artificial Neural Network (ANN) is applied to estimate the 
                         Integrated Water Vapor (IWV) of atmosphere, using HSB (Humidy 
                         Sensor Brazil) channels data from AQUA satellite, and simulations 
                         of the brightness temperatures from RTTOV-7. The intention of HSB 
                         is to obtain information of the content of water vapor in the 
                         atmosphere, precipitation, and when it is together instruments, 
                         such as: AMSU-A (Advanced Microwave Sounding Unit-A) and AIRS 
                         (Atmospheric Infrared Sounder), also on board of the AQUA 
                         satellite, they allow to infer soundings of atmospheric profiles 
                         of temperature and moisture under conditions of clear and cloudy 
                         sky. The HSB is a sensor with the same characteristics of the 
                         sounder AMSU-B that is on board of the satellites of the series 
                         NOAA-KLM, then this method can applied with that data. This paper 
                         shows the ANN as a new method to estimate IWV, with supervised 
                         training of observations data from the RACCI/LBA experiment in 
                         Rond{\^o}nia/Brazil, during period of September and October 2002. 
                         The Total IWV is also compared against radiosonde data, where all 
                         of the results are in good agreement with RMS differences less 
                         than 4 mm and biases less than 1 mm. This method can also used to 
                         estimate the variability of distribution of water vapor in 
                         atmosphere through the on-line update training process. The total 
                         precipitable water in Kg/m2 is near to the integrated values of 
                         the profiles of absolute moisture of the radiosondes of the 
                         experiment RaCCI/LBA.. In Southern Hemisphere, there is a big 
                         disadvantage, because the space and temporary distribution of the 
                         observations is weak. This method allows the estimate of the IWV 
                         to connect straightly the temperature of brilliance with the 
                         quantity of water vapor (for a determined vertical profile of 
                         temperature). These observations are important in weather 
                         forecast, like observation of moisture field of initial conditions 
                         for the numerical models, through the Data Assimilation to obtain 
                         homogeneous fields of the analysis. Since the conventional 
                         observations for radiosonde offer quite limited space covering, 
                         particularly in the South America, then there is a method of 
                         estimate of water vapor in the atmosphere from satellite data, 
                         that it will improve the limitations of the meteorological 
                         observations of conventional stations.",
  conference-location = "Foz do Igua{\c{c}}u",
      conference-year = "24-28 Apr. 2006",
           copyholder = "SID/SCD",
             language = "en",
         organisation = "American Meteorological Society (AMS)",
                  ibi = "cptec.inpe.br/adm_conf/2005/",
                  url = "http://urlib.net/rep/cptec.inpe.br/adm_conf/2005/",
           targetfile = "11-15.pdf",
                 type = "Addressing gaps in SH observing systems",
        urlaccessdate = "31 out. 2020"